Utilities and Pagination

class Paginator:
    def __init__(self, method, *args, **kwargs):
        """
        Initialize paginator for a Client method.
        
        Parameters:
        - method (callable): Client method that returns paginated results
        - *args: Positional arguments for the method
        - **kwargs: Keyword arguments for the method
        """

    def flatten(self, limit=None):
        """
        Flatten paginated results into a single iterator.
        
        Parameters:
        - limit (int, optional): Maximum number of items to return
        
        Yields:
        Individual items from paginated responses
        """

    def get_next(self):
        """
        Get the next page of results.
        
        Returns:
        Response object with next page data, or None if no more pages
        """

    def get_previous(self):
        """
        Get the previous page of results.
        
        Returns:
        Response object with previous page data, or None if no previous pages
        """

import tweepy

client = tweepy.Client(bearer_token="your_bearer_token")

# Paginate through search results
paginator = tweepy.Paginator(
    client.search_recent_tweets,
    query="python programming",
    max_results=100,
    tweet_fields=["created_at", "public_metrics"]
)

# Get all results (flattened)
for tweet in paginator.flatten(limit=500):
    print(f"{tweet.created_at}: {tweet.text}")

# Manual pagination
for page in paginator:
    print(f"Page contains {len(page.data)} tweets")
    for tweet in page.data:
        print(f"  - {tweet.text[:50]}...")
    
    # Stop after 3 pages
    if paginator.current_page >= 3:
        break

# Paginate through user followers
follower_paginator = tweepy.Paginator(
    client.get_users_followers,
    id="783214",  # Twitter's user ID
    max_results=1000,
    user_fields=["public_metrics", "verified"]
)

# Count followers with high follower counts
high_influence_followers = 0
for follower in follower_paginator.flatten(limit=10000):
    if follower.public_metrics['followers_count'] > 1000:
        high_influence_followers += 1

print(f"High-influence followers: {high_influence_followers}")

class Cursor:
    def __init__(self, method, *args, **kwargs):
        """
        Initialize cursor for an API method.
        
        Parameters:
        - method (callable): API method that returns paginated results
        - *args: Positional arguments for the method
        - **kwargs: Keyword arguments for the method
        """

    def items(self, limit=None):
        """
        Iterate over individual items from paginated results.
        
        Parameters:
        - limit (int, optional): Maximum number of items to return
        
        Yields:
        Individual items (tweets, users, etc.)
        """

    def pages(self, limit=None):
        """
        Iterate over pages of results.
        
        Parameters:
        - limit (int, optional): Maximum number of pages to return
        
        Yields:
        Lists of items (one page at a time)
        """

import tweepy

# Initialize API with authentication
auth = tweepy.OAuth1UserHandler(
    consumer_key="your_consumer_key",
    consumer_secret="your_consumer_secret",
    access_token="your_access_token", 
    access_token_secret="your_access_token_secret"
)
api = tweepy.API(auth, wait_on_rate_limit=True)

# Paginate through user's timeline
cursor = tweepy.Cursor(api.user_timeline, screen_name="python", count=200)

# Get individual tweets
for tweet in cursor.items(limit=1000):
    print(f"{tweet.created_at}: {tweet.text}")

# Process pages of results
for page in cursor.pages(limit=5):
    print(f"Processing page with {len(page)} tweets")
    for tweet in page:
        # Process each tweet in the page
        pass

# Paginate through followers
follower_cursor = tweepy.Cursor(api.get_followers, screen_name="python", count=200)

# Count followers by location
location_counts = {}
for follower in follower_cursor.items(limit=5000):
    location = follower.location or "Unknown"
    location_counts[location] = location_counts.get(location, 0) + 1

print("Top locations:")
for location, count in sorted(location_counts.items(), key=lambda x: x[1], reverse=True)[:10]:
    print(f"  {location}: {count}")

class Cache:
    """Base cache interface."""
    
    def get(self, key):
        """
        Get cached value by key.
        
        Parameters:
        - key (str): Cache key
        
        Returns:
        Cached value or None if not found
        """
        
    def store(self, key, value):
        """
        Store value in cache.
        
        Parameters:
        - key (str): Cache key
        - value: Value to cache
        """
        
    def cleanup(self):
        """Clean up expired cache entries."""

class MemoryCache(Cache):
    def __init__(self, timeout=60):
        """
        Initialize in-memory cache.
        
        Parameters:
        - timeout (int): Cache entry timeout in seconds
        """

class FileCache(Cache):
    def __init__(self, cache_dir, timeout=60):
        """
        Initialize file-based cache.
        
        Parameters:
        - cache_dir (str): Directory to store cache files
        - timeout (int): Cache entry timeout in seconds
        """

import tweepy

# Use memory cache with API
cache = tweepy.MemoryCache(timeout=300)  # 5 minute timeout
api = tweepy.API(auth, cache=cache)

# First call hits the API
user1 = api.get_user(screen_name="python")

# Second call uses cached result (if within timeout)
user2 = api.get_user(screen_name="python")  # Cached!

# Use file cache for persistent caching
file_cache = tweepy.FileCache(cache_dir="/tmp/tweepy_cache", timeout=3600)
api_with_file_cache = tweepy.API(auth, cache=file_cache)

# Cached results persist between application runs
user = api_with_file_cache.get_user(screen_name="python")

from collections import namedtuple

Response = namedtuple("Response", ("data", "includes", "errors", "meta"))
StreamResponse = namedtuple("StreamResponse", ("data",))

# API v2 responses use Response namedtuple
response = client.search_recent_tweets(query="python", max_results=10)

# Access primary data
tweets = response.data
print(f"Found {len(tweets)} tweets")

# Access included data (related objects)
if response.includes:
    users = response.includes.get('users', [])
    media = response.includes.get('media', [])
    
# Access response metadata
if response.meta:
    result_count = response.meta.get('result_count')
    next_token = response.meta.get('next_token')
    print(f"Total results: {result_count}")

# Handle errors
if response.errors:
    for error in response.errors:
        print(f"API Error: {error}")

class TweepyException(Exception):
    """Base exception class for all Tweepy errors."""

class HTTPException(TweepyException):
    """HTTP-related exceptions with response information."""
    
    def __init__(self, response):
        self.response = response
        self.api_errors = []  # API error details
        self.api_codes = []   # API error codes

class BadRequest(HTTPException):
    """400 Bad Request - Invalid request parameters."""

class Unauthorized(HTTPException):
    """401 Unauthorized - Authentication failure."""

class Forbidden(HTTPException):
    """403 Forbidden - Access denied."""

class NotFound(HTTPException):
    """404 Not Found - Resource not found."""

class TooManyRequests(HTTPException):
    """429 Too Many Requests - Rate limit exceeded."""

class TwitterServerError(HTTPException):
    """500+ Server Error - Twitter server issues."""

import tweepy

try:
    # API call that might fail
    tweet = client.create_tweet(text="Hello World!")
    
except tweepy.BadRequest as e:
    print(f"Bad request: {e}")
    if e.api_errors:
        for error in e.api_errors:
            print(f"  - {error['title']}: {error['detail']}")
            
except tweepy.Unauthorized as e:
    print("Authentication failed - check your credentials")
    
except tweepy.Forbidden as e:
    print("Access denied - insufficient permissions")
    
except tweepy.TooManyRequests as e:
    print("Rate limit exceeded - wait before retrying")
    
except tweepy.NotFound as e:
    print("Resource not found")
    
except tweepy.TwitterServerError as e:
    print(f"Twitter server error: {e.response.status_code}")
    
except tweepy.HTTPException as e:
    print(f"HTTP error {e.response.status_code}: {e}")
    
except tweepy.TweepyException as e:
    print(f"Tweepy error: {e}")

# API v2 Client with rate limit handling
client = tweepy.Client(
    bearer_token="your_bearer_token",
    wait_on_rate_limit=True  # Automatically wait when rate limited
)

# API v1.1 with rate limit handling
api = tweepy.API(auth, wait_on_rate_limit=True)

# Manual rate limit checking (v1.1 only)
def check_rate_limit():
    rate_limit_status = api.get_rate_limit_status()
    
    # Check specific endpoint limits
    search_limit = rate_limit_status['resources']['search']['/search/tweets']
    remaining = search_limit['remaining']
    reset_time = search_limit['reset']
    
    print(f"Search API calls remaining: {remaining}")
    print(f"Rate limit resets at: {reset_time}")

check_rate_limit()

# Configure global settings
tweepy.client.Client.DEFAULT_TIMEOUT = 30  # Default request timeout
tweepy.api.API.DEFAULT_RETRY_DELAY = 5     # Default retry delay

# Custom user agent
custom_client = tweepy.Client(
    bearer_token="your_bearer_token",
    user_agent="MyApp/1.0"
)

# Configure proxy settings
proxied_client = tweepy.Client(
    bearer_token="your_bearer_token",
    proxy="http://proxy.example.com:8080"
)